Coronary Artery DiseaseNCT03980470
Deep-Learning Image Reconstruction in CCTA
A study testing TrueFidelity in people with Coronary Artery Disease, run by University of Zurich at 1 site in Switzerland.
Trial summary
Cardiac CT allows the assessment of the heart and of the coronary arteries by use of ionising radiation. Although radiation exposure was significantly reduced in recent years, further decrease in radiation exposure is limited by increased image noise and deterioration in image quality. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Coronary Artery Disease
- What is being tested?
- TrueFidelity
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 50 participants
- Where
- 1 siteSwitzerland
- Study dates
- 8 May 2019to 20 Jun 2019
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Patients referred for cardiac CT angiography
- Age ≥ 18 years
- Written informed consent
Who cannot join
- Pregnancy or breast-feeding
- Enrollment of the investigator, his/her family members, employees and other dependent persons
- Renal insufficiency (GFR below 35 mL/min/1.73 m²)
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Usefulness of Deep-Learning Image Reconstruction for Cardiac Computed Tomography Angiography - a Prospective, Non-randomized Observational Trial
Cardiac CT allows the assessment of the heart and of the coronary arteries by use of ionising radiation. Although radiation exposure was significantly reduced in recent years, further decrease in radiation exposure is limited by increased image noise and deterioration in image quality. Recent evidence suggests that further technological refinements with artificial intelligence allows improved post-processing of images with reduction of image noise.
The present study aims at assessing the potential of a deep-learning image reconstruction algorithm in a clinical setting. Specifically, after a standard clinical scan, patients are scanned with lower radiation exposure and reconstructed with the DLIR algorithm. This interventional scan is then compared to the standard clinical scan.
- Conditions
- Coronary Artery Disease
- Being tested
- TrueFidelity
- Medical subject headings
- Coronary Artery Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
TrueFidelityDevice
TrueFidelity (Deep Learning Image Reconstruction, DLIR) software by GE Healthcare.
The medical device in question is a novel reconstruction algorithm for raw CT data which is based on artificial intelligence approaches, namely deep-learning iterative reconstruction (DLIR). This DLIR algorithm will be installed on the console of the CT Revolution scanning device, which is in routine clinical use for cardiac CT scans at the Department of Nuclear Medicine at the University Hospital Zurich. Purpose of this installation is the assessment of the performance of the DLIR algorithm during a limited time span of six weeks.
The algorithm will be CE-marked at the time of installation and use (statement by GE Healthcare provided separately). Its intended use is the reconstruction of CT datasets.
Of note, the novel DLIR algorithm will not substitute any clinical routine procedures currently in use. That is, diagnosis will still be made using the standard reconstruction algorithms.
| Study group | Role | What they receive |
|---|---|---|
| Normal-dose versus Low-dose | Other | The standard intervention consists of the routinely performed cardiac CT datasets reconstructed with a standard iterative reconstruction algorithm (ASIR-V). Median radiation dose is about 0.5 mSv, range between about 0.2 and 1.2 mSv; median contrast agent administration about 45 mL, range between 35 and 55 mL.
The experimental intervention is an additional CT scan with a lower dose (about 20 to 50% decrease) and a similar contrast agent administration that is reconstructed with a deep-learning image reconstruction immediately after the clinical CT scan. The additional time required is about 5 minutes. Receives: Device: TrueFidelity |
What is being measured
The primary outcome is the main question the study is designed to answer.
Subjective Image Quality
Subjective image quality as measured by Likert scale from 1 (non-evaluable) to 5 (excellent)
Measured: Day 1
Secondary outcomes (5)
Signal Intensity
Signal intensity as average hounsfield units within a region of interest in the aortic root, change from experimental interventional to the control intervention
Measured: Day 1
Image Noise
Image noise as standard deviation of hounsfield units within a region of interest in the aortic root, change from experimental interventional to the control intervention
Measured: Day 1
Signal-to-noise Ratio
Signal-to-noise ratio
Measured: Day 1
Dose-length Products
Comparison of dose-length products
Measured: Day 1
Plaque Volumes
Quantitative analysis of coronary artery plaque volumes
Measured: Day 1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Jun 2019
- Study start8 May 2019
- Primary completion20 Jun 2019
- Study completion20 Jun 2019
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for Coronary Artery DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 50 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Zurich
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Ronny R Buechel, MD, University of Zurich
- Investigators
- Ronny R Buechel, MD, Principal investigator, Director of Cardiac Imaging
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03980470
- Sponsor's protocol ID
- USZ-2019-00533
- Status last verified
- Oct 2021
- First submitted
- 24 May 2019
- Last updated
- 24 Nov 2021
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No
Publications
Benz DC, Grani C, Hirt Moch B, Mikulicic F, Vontobel J, Fuchs TA, Stehli J, Clerc OF, Possner M, Pazhenkottil AP, Gaemperli O, Buechel RR, Kaufmann PA. Minimized Radiation and Contrast Agent Exposure for Coronary Computed Tomography Angiography: First Clinical Experience on a Latest Generation 256-slice Scanner. Acad Radiol. 2016 Aug;23(8):1008-14. doi: 10.1016/j.acra.2016.03.015. Epub 2016 May 9.
PubMed 27174030Benz DC, Fuchs TA, Grani C, Studer Bruengger AA, Clerc OF, Mikulicic F, Messerli M, Stehli J, Possner M, Pazhenkottil AP, Gaemperli O, Kaufmann PA, Buechel RR. Head-to-head comparison of adaptive statistical and model-based iterative reconstruction algorithms for submillisievert coronary CT angiography. Eur Heart J Cardiovasc Imaging. 2018 Feb 1;19(2):193-198. doi: 10.1093/ehjci/jex008.
PubMed 28200212Sahiner B, Pezeshk A, Hadjiiski LM, Wang X, Drukker K, Cha KH, Summers RM, Giger ML. Deep learning in medical imaging and radiation therapy. Med Phys. 2019 Jan;46(1):e1-e36. doi: 10.1002/mp.13264. Epub 2018 Nov 20.
PubMed 30367497Toprak O. Conflicting and new risk factors for contrast induced nephropathy. J Urol. 2007 Dec;178(6):2277-83. doi: 10.1016/j.juro.2007.08.054. Epub 2007 Oct 22.
PubMed 17936812Benz DC, Grani C, Hirt Moch B, Mikulicic F, Vontobel J, Fuchs TA, Stehli J, Clerc OF, Possner M, Pazhenkottil AP, Gaemperli O, Buechel RR, Kaufmann PA. A low-dose and an ultra-low-dose contrast agent protocol for coronary CT angiography in a clinical setting: quantitative and qualitative comparison to a standard dose protocol. Br J Radiol. 2017 Jun;90(1074):20160933. doi: 10.1259/bjr.20160933. Epub 2017 May 25.
PubMed 28406318
Study at a glance
From the registry record, last updated by the sponsor on 24 Nov 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Usefulness of Deep-Learning Image Reconstruction for Cardiac Computed Tomography Angiography - a Prospective, Non-randomized Observational Trial
- ClinicalTrials.gov ID
- NCT03980470
- Acronym / sponsor ID
- USZ-2019-00533
- Conditions
- Coronary Artery Disease
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 50 participants (actual)
- Lead sponsor
- University of ZurichUniversity, hospital or other
- Study start
- 8 May 2019 (actual)
- Primary completion
- 20 Jun 2019 (actual)
- Study completion
- 20 Jun 2019 (actual)
- First posted
- 10 Jun 2019 (actual)
- Results
- Posted 24 Nov 2021
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Cardiac CT allows the assessment of the heart and of the coronary arteries by use of ionising radiation. Although radiation exposure was significantly reduced in recent years, further decrease in radiation exposure is limited by increased image noise and deterioration in image quality. Recent evidence suggests that further technological refinements with artificial intelligence allows improved post-processing of images with reduction of image noise.
The present study aims at assessing the potential of a deep-learning image reconstruction algorithm in a clinical setting. Specifically, after a standard clinical scan, patients are scanned with lower radiation exposure and reconstructed with the DLIR algorithm. This interventional scan is then compared to the standard clinical scan.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Normal-dose versus Low-dose | Other | Device: TrueFidelityThe standard intervention consists of the routinely performed cardiac CT datasets reconstructed with a standard iterative reconstruction algorithm (ASIR-V). Median radiation dose is about 0.5 mSv, range between about 0.2 and 1.2 mSv; median contrast agent administration about 45 mL, range between 35 and 55 mL. The experimental intervention is an additional CT scan with a lower dose (about 20 to 50% decrease) and a similar contrast agent administration that is reconstructed with a deep-learning image reconstruction immediately after the clinical CT scan. The additional time required is about 5 minutes. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Patients referred for cardiac CT angiography
- Age ≥ 18 years
- Written informed consent
Key exclusion criteria (3 listed)
- Pregnancy or breast-feeding
- Enrollment of the investigator, his/her family members, employees and other dependent persons
- Renal insufficiency (GFR below 35 mL/min/1.73 m²)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| TrueFidelityTrueFidelity (Deep Learning Image Reconstruction, DLIR) software by GE Healthcare. The medical device in question is a novel reconstruction algorithm for raw CT data which is based on artificial intelligence approaches, namely deep-learning iterative reconstruction (DLIR). This DLIR algorithm will be installed on the console of the CT Revolution scanning device, which is in routine clinical use for cardiac CT scans at the Department of Nuclear Medicine at the University Hospital Zurich. Purpose of this installation is the assessment of the performance of the DLIR algorithm during a limited time span of six weeks. The algorithm will be CE-marked at the time of installation and use (statement by GE Healthcare provided separately). Its intended use is the reconstruction of CT datasets. Of note, the novel DLIR algorithm will not substitute any clinical routine procedures currently in use. That is, diagnosis will still be made using the standard reconstruction algorithms. | Device | Normal-dose versus Low-dose |
Primary outcome
Subjective Image Quality
Time frame: Day 1
Subjective image quality as measured by Likert scale from 1 (non-evaluable) to 5 (excellent)
5 secondary outcomes
Signal Intensity
Time frame: Day 1
Image Noise
Time frame: Day 1
Signal-to-noise Ratio
Time frame: Day 1
Dose-length Products
Time frame: Day 1
Plaque Volumes
Time frame: Day 1
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Nov 2021.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Background: PubMed 27174030Benz DC, Grani C, Hirt Moch B, Mikulicic F, Vontobel J, Fuchs TA, Stehli J, Clerc OF, Possner M, Pazhenkottil AP, Gaemperli O, Buechel RR, Kaufmann PA. Minimized Radiation and Contrast Agent Exposure for Coronary Computed Tomography Angiography: First Clinical Experience on a Latest Generation 256-slice Scanner. Acad Radiol. 2016 Aug;23(8):1008-14. doi: 10.1016/j.acra.2016.03.015. Epub 2016 May 9.
- Background: PubMed 28200212Benz DC, Fuchs TA, Grani C, Studer Bruengger AA, Clerc OF, Mikulicic F, Messerli M, Stehli J, Possner M, Pazhenkottil AP, Gaemperli O, Kaufmann PA, Buechel RR. Head-to-head comparison of adaptive statistical and model-based iterative reconstruction algorithms for submillisievert coronary CT angiography. Eur Heart J Cardiovasc Imaging. 2018 Feb 1;19(2):193-198. doi: 10.1093/ehjci/jex008.
- Background: PubMed 30367497Sahiner B, Pezeshk A, Hadjiiski LM, Wang X, Drukker K, Cha KH, Summers RM, Giger ML. Deep learning in medical imaging and radiation therapy. Med Phys. 2019 Jan;46(1):e1-e36. doi: 10.1002/mp.13264. Epub 2018 Nov 20.
- Background: PubMed 17936812Toprak O. Conflicting and new risk factors for contrast induced nephropathy. J Urol. 2007 Dec;178(6):2277-83. doi: 10.1016/j.juro.2007.08.054. Epub 2007 Oct 22.
- Background: PubMed 28406318Benz DC, Grani C, Hirt Moch B, Mikulicic F, Vontobel J, Fuchs TA, Stehli J, Clerc OF, Possner M, Pazhenkottil AP, Gaemperli O, Buechel RR, Kaufmann PA. A low-dose and an ultra-low-dose contrast agent protocol for coronary CT angiography in a clinical setting: quantitative and qualitative comparison to a standard dose protocol. Br J Radiol. 2017 Jun;90(1074):20160933. doi: 10.1259/bjr.20160933. Epub 2017 May 25.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Ronny R Buechel, MD principal investigator
Director of Cardiac Imaging
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing TrueFidelity in people with Coronary Artery Disease, run by University of Zurich at 1 site in Switzerland.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 24 Nov 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Switzerland. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 24 Nov 2021). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Subjective Image Quality (time frame: Day 1). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03980470, which also lists 5 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Nov 2021; AzTrials last refreshed its copy on 27 Oct 2026.